Pattern detection based parameter adaptation

ABSTRACT

An integrated circuit that includes a feedback loop to adapt receiver parameters. The feedback loop includes a receiver to sample a signal and produce a sampled signal sequence. The feedback loop also includes a first pattern counter to detect and count occurrences of a first pattern in the sampled signal sequence, and a second pattern counter to detect and count occurrences of a second pattern in the sampled signal sequence. Control circuitry coupled to the receiver adapts a parameter value of the receiver to minimize a difference between a first ratio and a second ratio. The first ratio is a target ratio. The second ratio is between a first counted number of occurrences of the first pattern in the sampled signal sequence and a second counted number of occurrences of the second pattern in the sample signal sequence.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating a parameter adaptation system.

FIG. 2 is a block diagram illustrating a pattern ratio adaptationsystem.

FIG. 3 illustrates example sequences and search patterns.

FIGS. 4A-4B are a flowcharts illustrating methods of parameteradaptation.

FIG. 5A illustrates an example coarse adaptation of mean amplitude of areceived symbol based on the signal voltage distribution of an NRZ eyepattern.

FIG. 5B illustrates an example fine adaptation based on the signalvoltage distribution of an NRZ eye pattern.

FIG. 6 illustrates example parameter adaptations based on voltage marginof a four-level pulse amplitude modulation (PAM-4) eye pattern.

FIGS. 7A-7B illustrate example adaptations based on the voltage marginedges of a PAM-4 eye pattern.

FIG. 8A illustrates an example coarse adaptation based on the signalvoltage distribution of a PAM-4 eye pattern.

FIG. 8B illustrates a fine adaptation based on the signal voltagedistribution of a PAM-4 eye pattern.

FIG. 9 is a block diagram illustrating a processing system.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Serializer/Deserializer (SerDes) parameters such as receiver gains,continuous time linear equalization (CTLE) boost, symbol decisionthresholds, equalizer tap coefficients, DC offsets, etc. are iterativelyselected to track circuit variations which may be due to, for example,process, voltage, and temperature (PVT) variations. In an embodiment,various SerDes parameters are iteratively adjusted (adapted) based ondetected patterns. Two characteristic patterns (e.g., pattern A andpattern B) of samples and/or symbol decisions are selected such that,when a parameter is at its desired value, the patterns occur at a knownratio to each other. These characteristic patterns are concurrentlydetected and separately counted. The ratio of the occurrences of each ofthe characteristic patterns is compared to a target ratio to determineadjustments to the parameter being adjusted. When the ratio reaches thetarget ratio (or is within a selected tolerance range), the parameter isdetermined to be at its desired value. Selecting different patternsallows the adaptation of different parameters. This allows theadaptation circuit/system to optimize different SerDes parameters usinga common objective function (i.e., objective is to adjust the parameterto achieve a desired ratio of pattern A occurrences to pattern Boccurrences over a selected time window.)

FIG. 1 is a block diagram illustrating a parameter adaptation system. InFIG. 1, adaptation system 100 comprises input signal 150, receiver 110,pattern detector A 120, pattern detector B 121, pattern provision A 125,pattern provision B 126, pattern counter A 130, pattern counter B 131,feedback control 140, and parameter control signal 155. Receiver 110 maycomprise analog front-end (AFE) 111, sampler 112, digital equalizer 113,and symbol decision circuitry 114. Sampler 112 may, in some embodiments,include or comprise an analog-to-digital converter that outputs multipledigital bits. Feedback control 140 may, in some embodiments, include aprocessing system and/or software. Adaptation system 100 may beimplemented on one or more integrated circuits.

Input signal 150 is provided to at least receiver 110. Selected outputsand/or internal signals of receiver 110 are provided to pattern detectorA 120 and pattern detector B 121 (e.g., by multiplexor circuitry—notshown in FIG. 1.) For example, one or more of a sampler 112 output,digital equalizer 113, and/or symbol decision circuitry 114, and/orother signals internal to receiver 110 may be selected (e.g., byfeedback control 140) and provided to pattern detector A 120 and patterndetector B 121. Pattern detector A 120 receives a pattern (e.g., patternA) from pattern provision A 125. Pattern detector B 121 receives apattern (e.g., pattern B) from pattern provision B 126.

Pattern provision A 125 and pattern provision B 126 provide the patternsto be detected to pattern detector A 120 and pattern detector B 121,respectively. The patterns provided by pattern provision A 125 andpattern provision B 126 may be programmable. For example, patternprovision A 125 and pattern provision B 126 may comprise one or morewritable registers whose contents define the patterns to be detected. Inanother example, pattern provision A 125 and pattern provision B 126 maycomprise a plurality of fixed valued circuitry and/or read-onlyregisters whose values are selected by one or more control signals (notshown in FIG. 1.) In an embodiment, feedback control 140 may selectand/or program the patterns provided by one or more of pattern provisionA 125 and/or pattern provision B 126.

Pattern detector A 120 searches the outputs of receiver 110 for thepattern provided by pattern provision A 125 and signals pattern counterA 130 when that pattern occurs. Pattern counter A 130 receives anindicator from pattern detector A 120 that the pattern from patternprovision A 125 has occurred in the outputs from receiver 110. Patterncounter A 130 counts the number of occurrences of the pattern frompattern provision A 125 and provides that count to feedback control 140.Pattern counter A 130 may provide feedback control 140 with the numberof occurrences of the pattern from pattern provision A 125 as a singlenumber of occurrences that occurred over a selected time window. Patterncounter A 130 may provide feedback control 140 with a running total ofthe number of occurrences of the pattern from pattern provision A 125.

Pattern detector B 121 searches the outputs of receiver 110 for thepattern provided by pattern provision B 126 and signals pattern counterB 131 when that pattern occurs. Pattern counter B 131 receives anindicator from pattern detector B 121 that the pattern from patternprovision B 126 has occurred in the outputs from receiver 110. Patterncounter B 131 counts the number of occurrences of the pattern frompattern provision B 126 and provides that count to feedback control 140.Pattern counter B 131 may provide feedback control 140 with the numberof occurrences of the pattern from pattern provision B 126 as a singlenumber of occurrences that occurred over a selected time window. Patterncounter B 131 may provide feedback control 140 with a running total ofthe number of occurrences of the pattern from pattern provision B 126.

Based on the number of occurrences of the pattern from pattern provisionA 125 and the number of occurrences of the pattern from patternprovision B 126, feedback control 140 generates a parameter controlsignal 155. Parameter control signal 155 is provided to receiver 110.The receiver 110 parameter controlled by parameter control signal 155may be selectable (e.g., by feedback control 140 or a host system—notshown in FIG. 1.) Parameter control signal 155 may be selected tocontrol, for example, one or more sampler thresholds, sampler offsets,analog gains, receiver gains, continuous time linear equalization (CTLE)boost, other CTLE parameters, symbol decision thresholds, equalizer tapcoefficients, DC offsets, an analog FFE tap values, and/or analog DFEtap values before the samplers, and/or digital equalizer tap valuesafter one or more ADC type samplers.

Thus, it should be understood that parameter control signal 155 affectsa parameter of receiver 110 which, in turn affects one or more valuesoutput by receiver 110 in response to input signal 150. The valuesoutput by receiver 110 affect how many times the pattern being searchedfor by pattern detector A 120 (e.g., pattern A) is detected and therebycounted by pattern counter A 130. Likewise, the values output byreceiver 110 affect how many times the pattern being searched for bypattern detector B 121 (e.g., pattern B) is detected and thereby countedby pattern counter B 131. The counts output by pattern counter A andpattern counter B are provided to feedback control 140. Feedback control140 bases one or more new parameter control signals 155 on the countsoutput by pattern counter A and pattern counter B thereby completing afeedback loop with the provision of one or more new parameter controlsignals 155 to receiver 110.

Feedback control 140 iteratively generates adjusted values of parametercontrol signal 155 to minimize (or maximize) an objective function thatis based on the number of occurrences received from pattern counter A130 and the number of occurrences received from pattern counter B 131.For example, feedback control 140 may multiply pattern counter B 131'soutput with a target ratio (e.g., r_(target)). This target ratio is theobjective feedback control 140 seeks between the pattern A (provided bypattern provision A 125) occurrence statistics and the pattern B(provided by pattern provision A 125) occurrence statistics at theconvergence of adaptation/adjustment.

Feedback control 140 may calculate or determine an adjustment to theparameter being adapted based on a difference between the current ratioof occurrences to the target ratio of occurrences (r_(target)). Forexample, feedback control 140 may integrate the difference between thetarget ration and the current ratio to calculate the value of aparameter being adjusted during adaptation. Feedback control 140 mayalso include one or more of a timer to set the duration for patternstatistics evaluation, a finite state machine (FSM) to control the flowof pattern statistics evaluation, and a master FSM to control theoverall flow for adaptation and/or eye monitoring.

Adaptation system 100, therefore, may be used to implement one or moreof the following adaptation functions: signal detection, mean amplitudeof received symbols, symbol decision thresholds, analog front-end (AFE)gain control, AFE boost parameters, equalizer taps, AFE DC offset,sampler DC offset, eye edge detection, eye monitoring, and the like.

As discussed herein, feedback control 140 may iteratively generateadjusted values of parameter control signal 155 to minimize (ormaximize) an objective function that is based on the number ofoccurrences received from pattern counter A 130 and the number ofoccurrences received from pattern counter B 131. In an example, let grepresent a parameter to be adapted. The parameter g may be adjustedduring adaptation such that the ratio between the number of occurrencesof pattern A from pattern provision A 125 and the number of occurrenceof pattern B from pattern provision B 126 in a detection windowconverges to a target value—r_(target). The example objective functionimplemented by feedback control 140 can be written as minimizing theexpectation of the difference in the number of patterns detected. Inother words:

$\min\limits_{g}\left\{ {E{{{N_{a}(k)} - {{N_{b}(k)}r_{target}}}}^{2}} \right\}$

where N_(a)(k) and N_(b)(k) are the number of occurrences of pattern Aand the number of occurrences of pattern B detected in the kthevaluation window, and

$r_{target} = \frac{E{{N_{a}(k)}}}{E{{N_{b}(k)}}}$

is the target ratio when a parameter is adapted to its desired value.The difference in the occurrences of the two characteristic patterns isused to determine the adjustment at the end of a statistics evaluationwindow. In an embodiment, let e(k)=N_(a)(k)−N_(b)(k)r_(target), theparameter g(k) at discrete time k is given by

g(k) = g(k − 1) − usign[e(k)] where${{sign}\left\lbrack {e(k)} \right\rbrack} = \left\{ \begin{matrix}{1,} & {{e(k)} > 0} \\{0,} & {{e(k)} = 0} \\{{- 1},} & {{e(k)} < 0}\end{matrix} \right.$

and u is the step size for updating the parameter being adapted. Inanother embodiment, a gradient descent type algorithm may be used toselect the adjustment. In other words, determine a first error e′(k)using the parameter value g′(k)=g(k−1)+Δ and a second error e″(k) usingthe parameter value g″(k)=g(k−1)−Δ, and then select the parameter valueg′(k) or g″(k) that is associated with the lesser of e′(k) and e″(k) tobe g(k).

FIG. 2 is a block diagram illustrating a pattern ratio adaptationsystem. In FIG. 2, adaptation system 200 comprises receiver 210,sequence generator 215, pattern detection A 220, pattern detector B 221,pattern counter A 230, pattern counter B 231, count scaler 241, errorsignal generator 242, integrator 243, and feedback control 245. Receiver210 may comprise analog front-end (AFE) 211, samplers 212, digitalequalizer 213, and symbol decision circuitry 214. Samplers 212 may, insome embodiments, include an adaptation sampler. Samplers 212 may, insome embodiments, include or comprise an analog-to-digital converterthat outputs multiple digital bits. Adaptation system 200 may beimplemented on one or more integrated circuits.

Input signal 250 is provided to receiver 210. A plurality of outputsignals 219 of receiver 210 are provided to sequence generator 215.Selected outputs and/or internal signals of receiver 210 are provided tosequence generator 215 (e.g., by multiplexor circuitry—not shown in FIG.2.) For example, one or more of a sampler 212 output, digital equalizer213, and/or symbol decision circuitry 214, and/or other signals internalto receiver 210 may be selected (e.g., by feedback control 245 and/or ahost processor—not shown in FIG. 2) and provided to sequence generator215. The selected output signals 219 of receiver 210 may include one ormore of symbol decisions, sign bits of data samples, and/or sign bitsfrom an adaptation sampler. Sequence generator 215 receives the selectedoutput signals 219 of receiver 210 and formats the outputs into anadaptation sequence that is provided to pattern detection A 220 andpattern detector B 221.

Reference is now made to FIG. 3. In FIG. 3, a sample sequence 302 ofsamples and/or symbol decisions are illustrated. Sample sequence 302includes symbol decisions/data samples corresponding top number ofpre-cursor decisions/samples (d_(n+p) to d_(n+1)), q number ofpost-cursor decisions/samples (d_(n−1) to d_(n−q)), a datadecision/sample (d_(n)) made at the cursor, and an adaptationdecision/sample (a_(n)) also made at the cursor by an adaptationsampler. In an example, sequence generator 215 appends the adaptationdecision/sample made at the cursor to the end of the sequence of datadecisions/samples d_(n+p) to d_(n−q) to form an adaptation sequence 304to be evaluated by pattern detectors 220 and 221. However, it should beunderstood that this location is arbitrary and the adaptationdecision/sample an made at the cursor by one or more adaptation samplersmay be placed in any consistent location in adaptation sequence 304. Inanother embodiment, additional adaptation samples (e.g., pre- and/orpost-cursor—a_(n+p) to a_(n−q)) may be included in adaptation sequence304 (e.g., interleaved with data samples d_(n+p) to d_(n−q).)

Returning now with reference to FIG. 2, pattern detector A 220 andpattern detector B 221 receive an adaptation sequence from sequencegenerator 215. Pattern provision A 225 and pattern provision B 226provide patterns to be detected to pattern detector A 220 and patterndetector B 221, respectively. The patterns provided by pattern provisionA 225 and pattern provision B 226 may be programmable. For example,pattern provision A 225 and pattern provision B 226 may comprise one ormore writable registers whose contents define the patterns to bedetected. In another example, pattern provision A 225 and patternprovision B 226 may comprise a plurality of fixed valued circuitryand/or read-only registers whose values are selected by one or morecontrol signals (not shown in FIG. 2.) In an embodiment, one of patternprovision A 225 and pattern provision B 226 may supply a pattern thatmasks all of the bits thereby matching all sequences. Providing thistype of pattern to one of pattern detector A 220 and pattern detector B221 causes adaptation system 200 to function in a single patterndetector configuration.

Pattern detector A 220 receives a search pattern (e.g., pattern A) frompattern provision A 225 and a search pattern mask (e.g., search patternmask A) from pattern mask provision A 227. Pattern detector B 221receives a search pattern (e.g., search pattern B) from patternprovision B 226 and a search pattern mask (e.g., pattern mask B) frompattern mask provision B 228. The search pattern mask provided bypattern mask provision A 227 and pattern mask provision B 228 may beprogrammable. For example, pattern mask provision A 227 and pattern maskprovision B 228 may comprise one or more writable registers whosecontents define which bits are to contribute to pattern detection. Inanother example, pattern mask provision A 227 and pattern mask provisionB 228 may comprise a plurality of fixed valued circuitry and/orread-only registers whose values are selected by one or more controlsignals (not shown in FIG. 2.)

The search pattern masks provided by search pattern mask provisions227-228 (e.g., m_(p+q) to m₀) determine which correspondingdecisions/samples d_(n+p) to d_(n−q) and are considered when determiningwhether a pattern has been detected by pattern detectors 220-221,respectively. In other words, if a given bit (e.g., m_(p+1)corresponding to the cursor data decision/sample d_(n)) in a searchpattern mask is set accordingly, then the corresponding bit in theadaptation sequence will or will not be considered (e.g., the cursordata decision/sample d_(n) will be considered if m_(p+1) is set to a‘1’, and will not be considered if m_(p+1) is set to a ‘0’.)

This is further illustrated in FIG. 3. In FIG. 3, search pattern A 306having decisions/samples from p^(a) _(p+q) to p^(a) ₀ is masked by thecorresponding bits in search pattern mask A 307 having masking bitsm^(a) _(p+q) to m^(a) ₀. Likewise, search pattern B 308 havingdecisions/samples from p^(b) _(p+q) to p^(b) ₀ is masked by thecorresponding bits in search pattern mask B 309 having masking bitsm^(b) _(p+q) to m^(b) ₀.

Returning now with reference to FIG. 2, pattern detector A 220 searchesthe adaptation sequence for the pattern provided by the combination ofpattern provision A 225 and pattern mask provision A 227. When thatpattern occurs, pattern detection A 220 signals pattern counter A 230.

Pattern counter A 230 receives indicators from pattern detector A 220when the searched for pattern has occurred. Pattern counter A 230 countsthe number of occurrences of the pattern over a window of timecontrolled by count window control 244. Pattern counter B 231 receivesindicators from pattern detector B 221 when the searched for pattern hasoccurred. Pattern counter B 231 counts the number of occurrences of thepattern over the window of time controlled by count window control 244.

The count from pattern counter B 231 is provided to count scaler 241.Count scaler 241 receives a target ratio control signal 259. Targetratio control signal 259 determines the scaling applied to the countfrom pattern counter B 231. In essence, target ratio control signal 259may be viewed as corresponding to r_(target) in the previously describedobjective function:

$\min\limits_{g}\left\{ {E{{{N_{a}(k)} - {{N_{b}(k)}r_{target}}}}^{2}} \right\}$

where N_(a)(k) and N_(b)(k) are the number of occurrences of pattern Aand the number of occurrences of pattern B detected in the kthevaluation window, and

$r_{target} = \frac{E{{N_{a}(k)}}}{E{{N_{b}(k)}}}$

is the target ratio when a parameter is adapted to its desired value.

The output of count scaler 241 is a scaled count 251 (i.e., scaled count251 equals r(k)=N_(b)(k)×r_(target)). Scaled count 251 and the countfrom pattern counter A 230 are provided to error signal generation 242.Error signal generation 242 subtracts scaled count 251 from the countfrom pattern counter A 230 to produce error signal 252. Thus, errorsignal generation 242 may be viewed as implementing the previouslydescribed error function:

e(k)=N _(a)(k)−N _(b)(k)r _(target).

Error signal 252 is optionally provided to integrator 243. The output253 of integrator 243 is provided to feedback control 245. Feedbackcontrol 245 generates parameter control signal 255. Parameter controlsignal 255 is provided to receiver 210. Thus, in an embodiment,integrator 243 and feedback control 245 may be viewed as implementingthe previously described functions to generate parameter control signalg(k) of:

g(k) = g(k − 1) − usign[e(k)] where${{sign}\left\lbrack {e(k)} \right\rbrack} = \left\{ \begin{matrix}{1,} & {{e(k)} > 0} \\{0,} & {{e(k)} = 0} \\{{- 1},} & {{e(k)} < 0}\end{matrix} \right.$

and u is the step size for updating the parameter being adapted and k isa current discrete time step and/or iteration. In another embodiment,integrator 243 and feedback control 245 may be viewed as implementing agradient decent type algorithm to generate parameter control signal g(k)by determining a first error e′(k) using the parameter valueg′(k)=g(k−1)+Δ, and a second error e″(k) using the parameter valueg″(k)=g(k−1)−Δ, and then selecting the parameter value g′(k) or g″(k)that is associated with the lesser of e′(k) and e″(k) to be g(k).

The receiver 210 parameter controlled by parameter control signal 255may be selectable (e.g., by feedback control 245 or a host system—notshown in FIG. 2.) Parameter control signal 255 may be selected tocontrol, for example, one or more sampler thresholds, sampler offsets,analog gains, receiver gains, continuous time linear equalization (CTLE)boost, other CTLE parameters, symbol decision thresholds, equalizer tapcoefficients, DC offsets, analog FFE tap values, and/or analog DFE tapvalues before the samplers, and/or digital equalizer tap values afterone or more ADC type samplers.

FIG. 4A is a flowchart illustrating a method of parameter adaptation.The steps illustrated in FIG. 4A may be performed by one or more ofadaptation system 100, and/or adaptation system 200. By a receiver, andwhile the receiver is operating using a parameter value, a first sampledsignal sequence is sampled (402). For example, an adaptation sampler anda data sampler of samplers 210, while being provided a first value forparameter control signal 255, may repeatedly sample input signal 250thereby generating an adaptation sequence of samples.

A first number of occurrences of a first pattern in the first sampledsequence is counted (404). For example, in response to signals frompattern detector A 220, pattern counter A 230 may count the number ofoccurrences, in the sequence from sequence generator 215, of the patternprovided by pattern A provision 225 and pattern mask A provision 227.

A second number of occurrences of a first pattern in the first sampledsequence is counted (406). For example, in response to signals frompattern detector B 221, pattern counter B 231 may count the number ofoccurrences, in the sequence from sequence generator 215, of the patternprovided by pattern provision B 226 and pattern mask provision B 228.

Based at least in part on the count of the first number of occurrencesand the count of the second number of occurrences, adjust the parametervalue (408). For example, count scaler 241, error signal generator 242,integrator 243, and feedback control 245 may, based on the count frompattern A counter 230 and the count from pattern counter B 231, select anew value for parameter control signal 255. The new value from parametercontrol signal 255 may be selected to reduce the difference between theratio of the count from pattern A counter 230 and the count from patterncounter B 231 and a target ratio (e.g., r_(target).)

FIG. 4B is a flowchart illustrating a method of parameter adaptation.The steps illustrated in FIG. 4B may be performed by one or more ofadaptation system 100, and/or adaptation system 200. By a receiver, andwhile the receiver is operating using a first parameter value, a firstsampled signal sequence is sampled (412). For example, an adaptationsampler and a data sampler of samplers 210, while being provided a firstvalue for parameter control signal 255, may repeatedly sample inputsignal 250 thereby generating an adaptation sequence of samples.

A first number of occurrences of a first pattern in the first sampledsequence is counted (414). For example, in response to signals frompattern detector A 220, pattern counter A 230 may count the number ofoccurrences, in the sequence from sequence generator 215, of the patternprovided by pattern A provision 225 and pattern mask A provision 227.

A second number of occurrences of a first pattern in the first sampledsequence is counted (416). For example, in response to signals frompattern detector B 221, pattern counter B 231 may count the number ofoccurrences, in the sequence from sequence generator 215, of the patternprovided by pattern provision B 226 and pattern mask provision B 228.

Based at least in part on a first difference between a target ratio anda first measured ratio, selecting a second parameter value to beprovided to the receiver to reduce the first difference between thetarget ratio and the first measured ratio, the measured ratio beingbased on the first number of occurrences of the first pattern in thefirst sampled signal sequence and the second number of occurrences ofthe second pattern in the first sampled signal sequence (418). Forexample, count scaler 241, error signal generator 242, integrator 243,and feedback control 245 may, based on the count from pattern A counter230 and the count from pattern counter B 231, select a new value forparameter control signal 255. The new value from parameter controlsignal 255 may be selected to reduce the difference between the ratio ofthe count from pattern A counter 230 and the count from pattern counterB 231 and a target ratio (e.g., r_(target).)

Herein, NRZ mode is treated as a case of PAM-4 mode by replicating each1-bit symbol to form a 2-bit symbol decision so a common architecturecan be used for both PAM-4 and NRZ modes. The symbol decisions for PAM-4and NRZ are as follows: s₀=00b corresponds to decision symbol for PAM-4transmit level (−3) or NRZ transmit level (−1); s₁=01b corresponds todecision symbol for PAM-4 transmit level (−1); s₂=10b corresponds todecision symbol for PAM-4 transmit level (+1); and s₃=11b corresponds todecision symbol for PAM-4 transmit level (+3) or NRZ transmit level(+1). Also, for the purposes of the following discussion, a mask bitvalue of ‘0’ corresponds to the corresponding pattern bit not beingconsidered when searching for a pattern, and a mask bit value of ‘1’corresponds to the corresponding pattern bit being considered whensearching for a pattern.

FIG. 5A illustrates an example coarse adaptation of mean amplitude ofreceived symbol (e.g., symbol s₃) based on the signal voltagedistribution of an NRZ eye pattern. The adaptation illustrated in FIG.5A may be performed by one or more elements of adaptation system 100and/or adaptation system 200. The parameter being adapted in FIG. 5A isV_(s3). Table 1 illustrates example search patterns and search patternmask configurations used for an initial adaptation of the amplitudelevel for symbol s₃ as illustrated in FIG. 5A. It should be understoodthat the patterns and pattern masks detailed in Table 1 correspond to apattern A that is found when a_(n)==1 (other bits are don't care) and apattern B that is found when a_(n)==0 (other bits are don't care). Thetarget ratio r_(target) is 0.25/(1−0.25)=1/3.

TABLE 1 Adaptation Sequence d_(n+p) d_(n+p−1) . . . d_(n) . . . d_(n−m). . . d_(n−q) a_(n) Pattern A 00 00 . . . 00 . . . 00 . . . 00 1 PatternA mask 00 00 . . . 00 . . . 00 . . . 00 1 Pattern B 00 00 . . . 00 . . .00 . . . 00 0 Pattern B mask 00 00 . . . 00 . . . 00 . . . 00 1

In another example (not shown in FIG. 5A), pattern B may be set to apattern that matches all sequences (i.e., all bits are don't care) whilepattern A is found when a_(n)==1 (other bits are don't care). In thisexample, r_(target) is 0.25/(1)=1/4.

FIG. 5B illustrates an example fine adaptation based on the signalvoltage distribution of an NRZ eye pattern. The adaptation illustratedin FIG. 5B may be performed by one or more elements of adaptation system100 and/or adaptation system 200. The parameter being adapted in FIG. 5Bis V_(s3). Table 2 illustrates example search patterns and searchpattern mask configurations used for a fine adaptation of the amplitudelevel for symbol s₃ as illustrated in FIG. 5B. It should be understoodthat the patterns and pattern masks detailed in Table 2 correspond to apattern A that is found when the symbol decision equals s₃ and a_(n)==1(other bits are don't care) and a pattern B that is found when thesymbol decision equals s₃ but a_(n)==0 (other bits are don't care).

TABLE 2 Adaptation Sequence d_(n+p) d_(n+p−1) . . . d_(n) . . . d_(n−m). . . d_(n−q) a_(n) Pattern A 00 00 . . . 11 . . . 00 . . . 00 1 PatternA mask 00 00 . . . 11 . . . 00 . . . 00 1 Pattern B 00 00 . . . 11 . . .00 . . . 00 0 Pattern B mask 00 00 . . . 11 . . . 00 . . . 00 1

FIG. 6 illustrates example parameter adaptations based on voltage marginof a four-level pulse amplitude modulation (PAM-4) eye pattern. Theadaptations illustrated in FIG. 6 may be performed by one or moreelements of adaptation system 100 and/or adaptation system 200. To adaptmultiple parameters, let g_(m) denote the mth parameter being adapted,the objective function for the adaptation of g_(m) is

$\max\limits_{g_{m}}\left\lbrack {V_{hi} - V_{lo}} \right\rbrack$

where V_(hi) and V_(lo) are the upper and lower edge of vertical eyeopening at a target bit error rate (BER). Using the top PAM-4 eye as anexample, V_(hi) and V_(lo) are adapted such that the expectation of thedifference between the measured BER, r_(ber), and a target rate,r_(target), is minimized

$\min\limits_{\{{V_{hi},V_{lo}}\}}\left\lbrack {E\left( {{{r_{ber}(k)} - r_{target}}} \right)} \right\rbrack$

where r_(ber)(k)=N_(a)(k)/N_(b)(k) at discrete time k is the ratio ofthe number of pattern A being detected to the number of pattern B beingdetected in an evaluation window.

FIGS. 7A-7B illustrate example adaptations based on the voltage marginedges of a PAM-4 eye pattern. The adaptations illustrated in FIGS. 7A-7Bmay be performed by one or more elements of adaptation system 100 and/oradaptation system 200. FIG. 7A illustrates the adaptation of V_(hi).Table 3 illustrates example search patterns and search pattern maskconfigurations used for V_(hi) as illustrated in FIG. 7A.

TABLE 3 Adaptation Sequence d_(n+p) d_(n+p−1) . . . d_(n) . . . d_(n−m). . . d_(n−q) a_(n) Pattern A 00 00 . . . 11 . . . 00 . . . 00 0 PatternA mask 00 00 . . . 11 . . . 00 . . . 00 1 Pattern B 00 00 . . . 11 . . .00 . . . 00 0 Pattern B mask 00 00 . . . 11 . . . 00 . . . 00 0

FIG. 7B illustrates the adaptation of V_(lo). Table 4 illustratesexample search patterns and search pattern mask configurations used forV_(lo) as illustrated in FIG. 7B.

TABLE 4 Adaptation Sequence d_(n+p) d_(n+p−1) . . . d_(n) . . . d_(n−m). . . d_(n−q) a_(n) Pattern A 00 00 . . . 10 . . . 00 . . . 00 0 PatternA mask 00 00 . . . 11 . . . 00 . . . 00 1 Pattern B 00 00 . . . 10 . . .00 . . . 00 0 Pattern B mask 00 00 . . . 11 . . . 00 . . . 00 0

An objective function for the adaptation of upper edge V_(hi) and thelower eye edge V_(lo) at a target BER can be rewritten as:

$\min\limits_{{v_{hi}{(k)}}/{v_{lo}{(k)}}}\left\{ {E{{{N_{a}(k)} - {{N_{b}(k)}r_{ber}}}}^{2}} \right\}$${N_{a}(k)} = \left\{ {{\begin{matrix}{{\sum\limits_{n = 0}^{N_{w} - 1}\ \left( {d_{n}=={s_{3}\mspace{14mu} {and}\mspace{14mu} a_{n}}==0} \right)},} & {{for}\mspace{14mu} {detecting}\mspace{14mu} V_{hi}} \\{{\sum\limits_{n = 0}^{N_{w} - 1}\ \left( {d_{n}=={s_{2}\mspace{14mu} {and}\mspace{14mu} a_{n}}==1} \right)},} & {{for}\mspace{14mu} {detecting}\mspace{14mu} V_{lo}}\end{matrix}{N_{b}(k)}} = \left\{ \begin{matrix}{{\sum\limits_{n = 0}^{N_{w} - 1}\left( {d_{n}==s_{3}} \right)},} & {{for}\mspace{14mu} {detecting}\mspace{14mu} V_{hi}} \\{{\sum\limits_{n = 0}^{N_{w} - 1}\left( {d_{n}==s_{2}} \right)},} & {{for}\mspace{14mu} {detecting}\mspace{14mu} V_{lo}}\end{matrix} \right.} \right.$

To measure V_(hi) and V_(lo) using the adaptation system 100 and/oradaptation system 200, let r_(target)=r_(ber). Each parameter is adaptedby finding its optimum which leads to the maximum voltage margin at atarget BER. For example, the PAM-4 decision threshold between symbol s₃and s₂ is given by:

${V_{top}(k)} = \frac{{V_{hi}(k)} + {V_{lo}(k)}}{2}$

which is the symbol decision threshold between symbol s₃ and s₂ at thetarget BER. Other parameters such AFE boost and gains, the voltagemargins at different settings, etc. may be evaluated. The settings whichlead to the maximum voltage margin at a target BER may be selected asthe optimum set of settings.

In an embodiment, equalizer tap coefficients may be adapted by one ormore elements of adaptation system 100 and/or adaptation system 200.Adaptation system 100 and/or adaptation system 200 may optimize to anobjective function that decorrelates the data at the input of anequalizer and symbol decision error. For example, pattern A and patternB may be configured to detect positive correlation and negativecorrelation of the input of an equalizer and symbol decision error. Toadapt the mth equalizer tap (e.g., m∈{−p, −p+1, . . . , −1, 0, 1, . . ., q}), the coefficient of the mth tap is adapted to decorrelate the mthdata sample from main cursor at an equalizer input and the sign bit ofmain cursor's sample amplitude error (main cursor's sample amplitudeerror is the difference between the sampled main cursor's amplitude andthe corresponding mean amplitude of data samples which have the samesymbol being detected). In particular:

$\min\limits_{h_{m}{(k)}}\left\lbrack {E\left( {{{{sign}\left\lbrack {x_{n - m}(k)} \right\rbrack}*{{sign}\left( {e_{n}(k)} \right)}}} \right)} \right\rbrack$

where x_(n−m)(k) is the mth data sample from main cursor. Signale_(n)(k) is the corresponding sample amplitude error of main cursorsample x_(n)(k). To rewrite the objective function, let d_(n−n),=sign[x_(n−m)(k)] and symbol decision error a_(n)=sign(e_(n)(k)). Thisallows the objective function to be rewritten as

$\min\limits_{g_{m}{(k)}}\left\{ {E{{{N_{a}(k)} - {{N_{b}(k)}r_{target}}}}^{2}} \right\}$

where the target ratio r_(target) is 1 and

${N_{a}(k)} = {\sum\limits_{n = 0}^{N_{w} - 1}\left( {d_{n - m}=={1\mspace{14mu} {and}\mspace{14mu} a_{n}}==1} \right)}$${N_{b}(k)} = {\sum\limits_{n = 0}^{N_{w} - 1}\left( {d_{n - m}=={1\mspace{14mu} {and}\mspace{14mu} a_{n}}==0} \right)}$

Using feed-forward equalization (FFE) as an example, the mth FFE tap maybe adapted by adaptation system 100 and/or adaptation system 200 byusing the example pattern A and pattern B give in Table 5.

TABLE 5 Adaptation Sequence d_(n+p) d_(n+p−1) . . . d_(n) . . . d_(n−m). . . d_(n−q) a_(n) Pattern A 00 00 . . . 00 . . . 01 . . . 00 1 PatternA mask 00 00 . . . 00 . . . 01 . . . 00 1 Pattern B 00 00 . . . 00 . . .01 . . . 00 0 Pattern B mask 00 00 . . . 00 . . . 01 . . . 00 1

FIG. 8A illustrates an example coarse adaptation based on the signalvoltage distribution of a PAM-4 eye pattern. The adaptation illustratedin FIG. 8A may be performed by one or more elements of adaptation system100 and/or adaptation system 200. The parameter being adapted in FIG. 8Ais V_(s3). Table 6 illustrates example search patterns and searchpattern mask configurations used for an initial adaptation of theamplitude level for symbol s₃ illustrated in FIG. 8A. It should beunderstood that the patterns and pattern masks detailed in Table 6correspond to a pattern A that is found when a_(n)==1 (other bits aredon't care) and a pattern B that is found when a_(n)==0 (other bits aredon't care). The target ratio r_(target) is 0.125/(1−0.125)=1/7.

TABLE 6 Adaptation Sequence d_(n+p) d_(n+p−1) . . . d_(n) . . . d_(n−m). . . d_(n−q) a_(n) Pattern A 00 00 . . . 00 . . . 00 . . . 00 1 PatternA mask 00 00 . . . 00 . . . 00 . . . 00 1 Pattern B 00 00 . . . 00 . . .00 . . . 00 0 Pattern B mask 00 00 . . . 00 . . . 00 . . . 00 1

FIG. 8B illustrates a fine adaptation based on the signal voltagedistribution of a PAM-4 eye pattern. The adaptation illustrated in FIG.8B may be performed by one or more elements of adaptation system 100and/or adaptation system 200. The parameter being adapted in FIG. 8B isV_(s3). Table 7 illustrates example search patterns and search patternmask configurations used for a fine adaptation of the amplitude levelfor symbol s₃ illustrated in FIG. 8B. It should be understood that thepatterns and pattern masks detailed in Table 7 correspond to a pattern Athat is found when the symbol decision equals s₃ and a_(n)==1 (otherbits are don't care) and a pattern B that is found when the symboldecision equals s₃ but a_(n)==0 (other bits are don't care). The targetratio r_(target) is 0.5/(1−0.5)=1.

TABLE 7 Adaptation Sequence d_(n+p) d_(n+p−1) . . . d_(n) . . . d_(n−m). . . d_(n−q) a_(n) Pattern A 00 00 . . . 11 . . . 00 . . . 00 1 PatternA mask 00 00 . . . 11 . . . 00 . . . 00 1 Pattern B 00 00 . . . 11 . . .00 . . . 00 0 Pattern B mask 00 00 . . . 11 . . . 00 . . . 00 1

The methods, systems and devices described above may be implemented incomputer systems, or stored by computer systems. The methods describedabove may also be stored on a non-transitory computer readable medium.Devices, circuits, and systems described herein may be implemented usingcomputer-aided design tools available in the art, and embodied bycomputer-readable files containing software descriptions of suchcircuits. This includes, but is not limited to one or more elements ofadaptation system 100, and/or adaptation system 200, and theircomponents. These software descriptions may be: behavioral, registertransfer, logic component, transistor, and layout geometry-leveldescriptions. Moreover, the software descriptions may be stored onstorage media or communicated by carrier waves.

Data formats in which such descriptions may be implemented include, butare not limited to: formats supporting behavioral languages like C,formats supporting register transfer level (RTL) languages like Verilogand VHDL, formats supporting geometry description languages (such asGDSII, GDSIII, GDSIV, CIF, and MEBES), and other suitable formats andlanguages. Moreover, data transfers of such files on machine-readablemedia may be done electronically over the diverse media on the Internetor, for example, via email. Note that physical files may be implementedon machine-readable media such as: 4 mm magnetic tape, 8 mm magnetictape, 3½ inch floppy media, CDs, DVDs, and so on.

FIG. 9 is a block diagram illustrating one embodiment of a processingsystem 900 for including, processing, or generating, a representation ofa circuit component 920. Processing system 900 includes one or moreprocessors 902, a memory 904, and one or more communications devices906. Processors 902, memory 904, and communications devices 906communicate using any suitable type, number, and/or configuration ofwired and/or wireless connections 908.

Processors 902 execute instructions of one or more processes 912 storedin a memory 904 to process and/or generate circuit component 920responsive to user inputs 914 and parameters 916. Processes 912 may beany suitable electronic design automation (EDA) tool or portion thereofused to design, simulate, analyze, and/or verify electronic circuitryand/or generate photomasks for electronic circuitry. Representation 920includes data that describes all or portions of adaptation system 100,and/or adaptation system 200, and their components, as shown in theFigures.

Representation 920 may include one or more of behavioral, registertransfer, logic component, transistor, and layout geometry-leveldescriptions. Moreover, representation 920 may be stored on storagemedia or communicated by carrier waves.

Data formats in which representation 920 may be implemented include, butare not limited to: formats supporting behavioral languages like C,formats supporting register transfer level (RTL) languages like Verilogand VHDL, formats supporting geometry description languages (such asGDSII, GDSIII, GDSIV, CIF, and MEBES), and other suitable formats andlanguages. Moreover, data transfers of such files on machine-readablemedia may be done electronically over the diverse media on the Internetor, for example, via email

User inputs 914 may comprise input parameters from a keyboard, mouse,voice recognition interface, microphone and speakers, graphical display,touch screen, or other type of user interface device. This userinterface may be distributed among multiple interface devices.Parameters 916 may include specifications and/or characteristics thatare input to help define representation 920. For example, parameters 916may include information that defines device types (e.g., NFET, PFET,etc.), topology (e.g., block diagrams, circuit descriptions, schematics,etc.), and/or device descriptions (e.g., device properties, devicedimensions, power supply voltages, simulation temperatures, simulationmodels, etc.).

Memory 904 includes any suitable type, number, and/or configuration ofnon-transitory computer-readable storage media that stores processes912, user inputs 914, parameters 916, and circuit component 920.

Communications devices 906 include any suitable type, number, and/orconfiguration of wired and/or wireless devices that transmit informationfrom processing system 900 to another processing or storage system (notshown) and/or receive information from another processing or storagesystem (not shown). For example, communications devices 906 may transmitcircuit component 920 to another system. Communications devices 906 mayreceive processes 912, user inputs 914, parameters 916, and/or circuitcomponent 920 and cause processes 912, user inputs 914, parameters 916,and/or circuit component 920 to be stored in memory 904.

Implementations discussed herein include, but are not limited to, thefollowing examples:

Example 1

An integrated circuit, comprising: at least one receiver to sample asignal and produce a sampled signal sequence; a first pattern counter todetect and count occurrences of a first pattern in the sampled signalsequence; a second pattern counter to detect and count occurrences of asecond pattern in at least the sampled signal sequence; and, controlcircuitry to adapt a parameter value of the at least one receiver basedon the counted occurrences of the first pattern by the first patterncounter and the counted occurrences of the second pattern by the secondpattern counter.

Example 2

The integrated circuit of example 1, wherein the parameter value isadapted to minimize a difference between a first ratio and a secondratio, the second ratio to be between a first counted number ofoccurrences of the first pattern in the sampled signal sequence and asecond counted number of occurrences of the second pattern in the samplesignal sequence.

Example 3

The integrated circuit of example 2, wherein the first counted number ofoccurrences of the first pattern in the sampled signal sequence and thesecond counted number of occurrences of the second pattern are detectedin a window of consecutive samples in the sampled signal sequence.

Example 4

The integrated circuit of example 2, wherein the control circuitryincludes a finite state machine to receive an error indicatorcorresponding to the difference between the first ratio and the secondratio and to, based on the error indicator, select an adapted parametervalue.

Example 5

The integrated circuit of example 1, wherein the control circuitry iscoupled to at least one sampler of the receiver.

Example 6

The integrated circuit of example 1, wherein the at least one receivercomprises an adaptation sampler and a data sampler.

Example 7

The integrated circuit of example 6, wherein the sampled signal sequenceincludes a first at least one sample produced by the adaptation sampler.

Example 8

An integrated circuit, comprising: a receiver to produce a first set ofsequential data samples, the receiver to receive a first indicator of aparameter that affects at least one sampled value in the first set ofsequential data samples; a first pattern detector to signal occurrencesof a first pattern in at least the first set of sequential data samples;a first counter to count occurrences of the first pattern in at leastthe first set of sequential data samples; a second pattern detector tosignal occurrences of a second pattern in at least the first set ofsequential data samples; a second counter to count occurrences of thesecond pattern in at least the first set of sequential data samples;and, feedback loop control to iteratively adjust the parameter.

Example 9

The integrated circuit of example 8, wherein the feedback loop controliteratively adjusts the parameter to minimize a difference between atarget ratio and a measured occurrence ratio, the measured occurrenceratio to be between a first count of occurrences of the first pattern inthe first set of sequential data samples and a second count ofoccurrences of the second pattern the first set of sequential datasamples.

Example 10

The integrated circuit of example 8, further comprising: patternprovision circuitry to provide a first plurality of patterns to at leastthe first pattern detector.

Example 11

The integrated circuit of example 10, wherein at least a first one ofthe first plurality of patterns include at least one pattern maskindicator that indicates at least a portion of the first one of thefirst plurality of patterns is not to be used in a detection of anoccurrence of the first one of the first plurality of patterns in thefirst set of sequential data samples.

Example 12

The integrated circuit of example 10, further comprising: at least oneadaptation sampler to sample the signal and produce a second set ofsequential data samples.

Example 13

The integrated circuit of example 12, wherein at least one of the secondset of sequential data samples is included in the first set ofsequential data samples.

Example 14

The integrated circuit of example 12, wherein at least a first one ofthe first plurality of patterns include at least one pattern maskindicator that indicates at least a portion of the first one of thefirst plurality of patterns is not to be used in a detection of anoccurrence of the first one of the first plurality of patterns in thesecond set of sequential data samples.

Example 15

A method, comprising: sampling, by a receiver and while the receiver isoperating using a parameter value, a first sampled signal sequence;counting a first number of occurrences of a first pattern in the firstsampled signal sequence; counting a second number of occurrences of asecond pattern in the first sampled signal sequence; and, based at leastin part on a count of the first number of occurrences and a count of thesecond number of occurrences, adjusting the parameter value.

Example 16

The method of example 15, wherein based at least in part on a firstdifference between a target ratio and a measured ratio, a secondparameter value is selected to be provided to the at least one samplerto reduce the first difference between the target ratio and the measuredratio, the measured ratio being based on the first number of occurrencesof the first pattern in the first sampled signal sequence and the secondnumber of occurrences of the second pattern in the first sampled signalsequence.

Example 17

The method of example 16, further comprising: sampling, by the receiverand while the receiver is operating using the second parameter value, asecond sampled signal sequence; counting a third number of occurrencesof the first pattern in the second sampled signal sequence; counting afourth number of occurrences of the second pattern in the second sampledsignal sequence; and, based at least in part on a second differencebetween the target ratio and a second measured ratio, selecting a thirdparameter value to be provided to the receiver to reduce the seconddifference between the target ratio and the second measured ratio, thesecond measured ratio being based on the third number of occurrences ofthe first pattern in the second sampled signal sequence and the fourthnumber of occurrences of the second pattern in the second sampled signalsequence.

Example 18

The method of example 15, further comprising: sampling, by at least oneadaptation sampler, a second sampled signal sequence.

Example 19

The method of example 18, wherein the counting of the first number ofoccurrences of the first pattern is further based on a first at leastone sample of the second sampled signal sequence.

Example 20

The method of example 18, wherein the counting of the second number ofoccurrences of the second pattern is further based on a second at leastone sample of the second sampled signal sequence.

The foregoing description of the invention has been presented forpurposes of illustration and description. It is not intended to beexhaustive or to limit the invention to the precise form disclosed, andother modifications and variations may be possible in light of the aboveteachings. The embodiment was chosen and described in order to bestexplain the principles of the invention and its practical application tothereby enable others skilled in the art to best utilize the inventionin various embodiments and various modifications as are suited to theparticular use contemplated. It is intended that the appended claims beconstrued to include other alternative embodiments of the inventionexcept insofar as limited by the prior art.

What is claimed is:
 1. An integrated circuit, comprising: at least onereceiver to sample a signal and produce a sampled signal sequence; afirst pattern counter to detect and count occurrences of a first patternin the sampled signal sequence; a second pattern counter to detect andcount occurrences of a second pattern in at least the sampled signalsequence; and, control circuitry to adapt a parameter value of the atleast one receiver based on the counted occurrences of the first patternby the first pattern counter and the counted occurrences of the secondpattern by the second pattern counter.
 2. The integrated circuit ofclaim 1, wherein the parameter value is adapted to minimize a differencebetween a first ratio and a second ratio, the second ratio to be betweena first counted number of occurrences of the first pattern in thesampled signal sequence and a second counted number of occurrences ofthe second pattern in the sample signal sequence.
 3. The integratedcircuit of claim 2, wherein the first counted number of occurrences ofthe first pattern in the sampled signal sequence and the second countednumber of occurrences of the second pattern are detected in a window ofconsecutive samples in the sampled signal sequence.
 4. The integratedcircuit of claim 2, wherein the control circuitry includes a finitestate machine to receive an error indicator corresponding to thedifference between the first ratio and the second ratio and to, based onthe error indicator, select an adapted parameter value.
 5. Theintegrated circuit of claim 1, wherein the control circuitry is coupledto at least one sampler of the receiver.
 6. The integrated circuit ofclaim 1, wherein the at least one receiver comprises an adaptationsampler and a data sampler.
 7. The integrated circuit of claim 6,wherein the sampled signal sequence includes a first at least one sampleproduced by the adaptation sampler.
 8. An integrated circuit,comprising: a receiver to produce a first set of sequential datasamples, the receiver to receive a first indicator of a parameter thataffects at least one sampled value in the first set of sequential datasamples; a first pattern detector to signal occurrences of a firstpattern in at least the first set of sequential data samples; a firstcounter to count occurrences of the first pattern in at least the firstset of sequential data samples; a second pattern detector to signaloccurrences of a second pattern in at least the first set of sequentialdata samples; a second counter to count occurrences of the secondpattern in at least the first set of sequential data samples; and,feedback loop control to iteratively adjust the parameter.
 9. Theintegrated circuit of claim 8, wherein the feedback loop controliteratively adjusts the parameter to minimize a difference between atarget ratio and a measured occurrence ratio, the measured occurrenceratio to be between a first count of occurrences of the first pattern inthe first set of sequential data samples and a second count ofoccurrences of the second pattern the first set of sequential datasamples.
 10. The integrated circuit of claim 8, further comprising:pattern provision circuitry to provide a first plurality of patterns toat least the first pattern detector.
 11. The integrated circuit of claim10, wherein at least a first one of the first plurality of patternsinclude at least one pattern mask indicator that indicates at least aportion of the first one of the first plurality of patterns is not to beused in a detection of an occurrence of the first one of the firstplurality of patterns in the first set of sequential data samples. 12.The integrated circuit of claim 10, further comprising: at least oneadaptation sampler to sample the signal and produce a second set ofsequential data samples.
 13. The integrated circuit of claim 12, whereinat least one of the second set of sequential data samples is included inthe first set of sequential data samples.
 14. The integrated circuit ofclaim 12, wherein at least a first one of the first plurality ofpatterns include at least one pattern mask indicator that indicates atleast a portion of the first one of the first plurality of patterns isnot to be used in a detection of an occurrence of the first one of thefirst plurality of patterns in the second set of sequential datasamples.
 15. A method, comprising: sampling, by a receiver and while thereceiver is operating using a parameter value, a first sampled signalsequence; counting a first number of occurrences of a first pattern inthe first sampled signal sequence; counting a second number ofoccurrences of a second pattern in the first sampled signal sequence;and, based at least in part on a count of the first number ofoccurrences and a count of the second number of occurrences, adjustingthe parameter value.
 16. The method of claim 15, wherein based at leastin part on a first difference between a target ratio and a measuredratio, a second parameter value is selected to be provided to the atleast one sampler to reduce the first difference between the targetratio and the measured ratio, the measured ratio being based on thefirst number of occurrences of the first pattern in the first sampledsignal sequence and the second number of occurrences of the secondpattern in the first sampled signal sequence.
 17. The method of claim16, further comprising: sampling, by the receiver and while the receiveris operating using the second parameter value, a second sampled signalsequence; counting a third number of occurrences of the first pattern inthe second sampled signal sequence; counting a fourth number ofoccurrences of the second pattern in the second sampled signal sequence;and, based at least in part on a second difference between the targetratio and a second measured ratio, selecting a third parameter value tobe provided to the receiver to reduce the second difference between thetarget ratio and the second measured ratio, the second measured ratiobeing based on the third number of occurrences of the first pattern inthe second sampled signal sequence and the fourth number of occurrencesof the second pattern in the second sampled signal sequence.
 18. Themethod of claim 15, further comprising: sampling, by at least oneadaptation sampler, a second sampled signal sequence.
 19. The method ofclaim 18, wherein the counting of the first number of occurrences of thefirst pattern is further based on a first at least one sample of thesecond sampled signal sequence.
 20. The method of claim 18, wherein thecounting of the second number of occurrences of the second pattern isfurther based on a second at least one sample of the second sampledsignal sequence.